Insurance AI that processes documents, not just reads them.
We build AI systems that extract structured data from insurance documents, automate underwriting and claims workflows, and detect fraud - integrated with the core systems your operations team already runs.
Discuss your InsurTech build< 2 min
Submission-to-quote with underwriting AI
90%+
Straight-through processing rate on simple claims
40–60%
Reduction in document processing cost
Use cases
Underwriting Automation
Ingest structured and unstructured risk data - property surveys, financial statements, loss histories - and generate underwriting recommendations with supporting rationale. Reduces submission-to-quote time from days to minutes.
Claims Triage & Processing
First notice of loss classification, coverage verification, reserve estimation, and straight-through processing for simple claims. Complex claims flagged for adjuster review with pre-populated data packets.
Policy Document Intelligence
LLM-based extraction of policy terms, coverage limits, sublimits, exclusions, endorsements, and conditions from unstructured policy documents - normalised to a structured schema for downstream systems.
Fraud Detection
Anomaly detection on claims patterns, network analysis for organised fraud rings, and document authenticity verification - trained on insurance-specific fraud typologies.
Document AI deep dive
Insurance documents are complex, inconsistent, and full of legal language. Here is exactly what we extract - and how.
Extraction uses a hybrid approach: layout-aware document parsing, fine-tuned LLM extraction with schema constraints, and confidence scoring on every field. Low-confidence extractions are routed to human review queues automatically.
Underwriting AI
Inputs
Loss history
Property data
Financial statements
Third-party signals
Benchmark portfolios
Model
Risk scoring engine
Limit recommendation
Pricing adjustment
Referral triggers
Appetite checks
Output
Indication letter
Quote with rationale
Referred risk summary
Declination with reason
Audit trail
Compliance
GDPR & Data Retention
Personal data minimisation, retention schedules, right to erasure pipelines, and lawful basis documentation for all AI processing activities.
Adverse Action & Explainability
Where AI influences insurance decisions, we provide SHAP-based attribution and plain-language explanations suitable for adverse action notices.
Model Governance
Inventory of all production models, performance monitoring, drift alerts, and annual revalidation cycles - aligned to Solvency II and FCA model risk guidance.
Integration points
Guidewire
ClaimCenter and PolicyCenter integrations via REST API and Gosu customisation layers.
Duck Creek
Policy, billing, and claims module integrations with Duck Creek OnDemand and on-premise deployments.
Salesforce FS Cloud
Opportunity management, policy tracking, and AI-generated renewal communications.
Document Management
OpenText, SharePoint, and custom DMS integrations for policy and claims document workflows.
"Policy document extraction at 94% field accuracy - 3× faster submission turnaround for a Lloyd's syndicate."
LLM extraction pipeline processing 2,000+ policy documents per day across 14 coverage lines. Integrated with Guidewire PolicyCenter. Confidence-based routing reduced adjuster review volume by 61%.
Insurance AI - by the numbers
94%
Field extraction accuracy on multi-line policy documents
< 2 min
Submission-to-indication with underwriting AI
61%
Reduction in adjuster review volume via confidence-based routing
3×
Faster claims straight-through processing vs. manual workflows
The old way vs. the new way
Why legacy insurance ops can't scale
Architecture
How our claims AI pipeline works
01
FNOL Intake
Email, portal, or API submission captured and normalised
02
Document Parse
Layout-aware extraction of photos, PDFs, and claim forms
03
Coverage Verify
Policy retrieved and coverage terms matched to claim type
04
Reserve Estimate
ML reserve model estimates loss cost with confidence range
05
STP or Route
Simple claims closed automatically; complex claims routed with data packet
End-to-end pipeline latency: under 90 seconds for simple claims. Confidence thresholds are configurable per line of business. All decisions logged to an immutable audit trail integrated with Guidewire ClaimCenter.
Common questions
InsurTech AI - what clients ask us first
Can AI extraction handle non-standard policy wordings?
Yes. We use a hybrid of layout parsing and fine-tuned LLMs that generalise across bespoke wordings, manuscript endorsements, and non-standard structures. We validate against a test set from your document population before go-live.
How do you handle low-confidence extractions?
Every extracted field carries a confidence score. Fields below your configured threshold are automatically queued for human review with a pre-filled UI - reviewers confirm or correct, and feedback improves the model.
Is the underwriting AI explainable for regulatory purposes?
Yes. We output SHAP-based attribution for every risk score. The explanation identifies which input features drove the recommendation, making it suitable for adverse action notices and regulatory audit.
What does integration with Guidewire or Duck Creek look like?
We integrate via their published APIs and where needed through customisation layers (Gosu for Guidewire). Data flows bidirectionally - AI results write back into the core system, not just a side dashboard.
How long does a typical InsurTech AI engagement take to go live?
Document extraction pipelines typically reach production in 10–14 weeks. Underwriting AI with full integration takes 16–24 weeks depending on data quality and API access. We scope this precisely during discovery.